Data_Sheet_1_Association between omega-3/6 fatty acids and cholelithiasis: A mendelian randomization study.docx

BackgroundOmega-3 and omega-6 may be protective factors for cholelithiasis. However, this relationship has not yet been demonstrated clearly. Therefore, we attempted to identify these causal relationships.Materials and methodsThe omega-3/6 fatty acid discovery dataset was obtained from UK Biobank and contained 114,999 individuals. The validation set was derived from an independent genome-wide association study (GWAS) and contained 13,544 individuals. The cholelithiasis dataset was derived from FinnGen and contained 19,023 cases and 195,144 controls. The inverse variance weighting (IVW) method was used as the main method of analysis in this study. Multiple methods of analysis were also used in the repeated methods, including the MR-Egger, weighted median, MR-pleiotropic residual sum (MR-PRESSO), outliers, and maximum likelihood methods. In addition, we used multiple sensitivity analyses to identify the potential pleiotropy.ResultIn the discovery stage, the results of the random effect IVW analysis showed that higher omega-3 levels were correlated inversely with the risk of cholelithiasis (β = –0.22, 95% CI [–0.32 to –0.12], P = 1.49 × 10–5). When the replication analysis was performed using another set of instrumental variables (IVs), the causal relationship between omega-3 fatty acids and cholelithiasis remained stable (β = –0.42, 95% CI [–0.66 to –0.18], P = 5.49 × 10–4), except for the results obtained using the MR-Egger method, which were not significant. The results of the IVW approach showed that each SD increase in omega-6 levels was associated negatively with the risk of cholelithiasis, both in the discovery (β = –0.21, 95% CI [–0.35 to –0.06], P = 4.37 × 10–3) and the validation phases (β = –0.21, 95% CI [–0.40 to –0.02], P = 3.44 × 10–2).ConclusionThe results of our MR study suggest that omega-3/6 is associated with cholelithiasis risk. Attention to the risk of cholelithiasis in individuals with low serum omega-3/6 levels is necessary.</p

<i>P</i>-values of a two-way ANOVA for the effects of <i>Lactobacillus acidophilus</i>, time, and their interactions on the ten variables (N = 90).

<p>Note: MLCK: myosin light chain kinase; MLCP: myosin light chain phosphatase; PKC: protein kinase C; ICC numbers: the numbers of interstitial cells of Cajal.</p><p>*indicates a significant difference (<i>P</i> < 0.05)</p><p>**indicates a highly significant difference (<i>P</i> < 0.01).</p><p><i>P</i>-values of a two-way ANOVA for the effects of <i>Lactobacillus acidophilus</i>, time, and their interactions on the ten variables (N = 90).</p

<i>Lactobacillus acidophilus</i> restored the impaired ICC networks mediated by TBI.

<p>The ICC networks and numbers were detected under fluorescence microscope (400×) by immunofluorescence in ileal tissue sections. The interaction of <i>Lactobacillus acidophilus</i> and time on ICC numbers was not significant. (A) Low-density of ICC networks was observed after TBI compared with control. <i>Lactobacillus acidophilus</i> significantly restored TBI-mediated disruption of ICC networks. (B) The reduction of ICC numbers was also observed after TBI, **<i>P</i> < 0.01 compared with control. <i>Lactobacillus acidophilus</i> significantly restored TBI-mediated reduction of ICC numbers, #<i>P</i> < 0.05 compared with TBI.</p

Image_1_Cuproptosis depicts tumor microenvironment phenotypes and predicts precision immunotherapy and prognosis in bladder carcinoma.tiff

BackgroundThough immune checkpoint inhibitors (ICIs) exhibit durable efficacy in bladder carcinomas (BLCAs), there are still a large portion of patients insensitive to ICIs treatment.MethodsWe systematically evaluated the cuproptosis patterns in BLCA patients based on 46 cuproptosis related genes and correlated these cuproptosis patterns with tumor microenvironment (TME) phenotypes and immunotherapy efficacies. Then, for individual patient’s evaluation, we constructed a cuproptosis risk score (CRS) for prognosis and a cuproptosis signature for precise TME phenotypes and immunotherapy efficacies predicting.ResultsTwo distinct cuproptosis patterns were generated. These two patterns were consistent with inflamed and noninflamed TME phenotypes and had potential role for predicting immunotherapy efficacies. We constructed a CRS for predicting individual patient’s prognosis with high accuracy in TCGA-BLCA. Importantly, this CRS could be well validated in external cohorts including GSE32894 and GSE13507. Then, we developed a cuproptosis signature and found it was significantly negative correlated with tumor-infiltrating lymphocytes (TILs) both in TCGA-BLCA and Xiangya cohorts. Moreover, we revealed that patients in the high cuproptosis signature group represented a noninflamed TME phenotype on the single cell level. As expected, patients in the high cuproptosis signature group showed less sensitive to immunotherapy. Finally, we found that the high and low cuproptosis signature groups were consistent with luminal and basal subtypes of BLCA respectively, which validated the role of signature in TME in terms of molecular subtypes.ConclusionsCuproptosis patterns depict different TME phenotypes in BLCA. Our CRS and cuproptosis signature have potential role for predicting prognosis and immunotherapy efficacy, which might guide precise medicine.</p

<i>Lactobacillus acidophilus</i> improved the contractile activity of intestinal smooth muscle impaired by TBI.

<p>Ninety C57BL/6 mice were randomly divided into three groups including control, TBI and TBI + <i>Lactobacillus acidophilus</i> groups. The interaction of <i>Lactobacillus acidophilus</i> and time on intestinal contractile activity was not significant. (A) The contractile activity was determined by histologic and physiologic analyses. (B) The average contractile amplitude was decreased after TBI, **<i>P</i> < 0.01 compared with control. <i>Lactobacillus acidophilus</i> could increase in contractile amplitude, #<i>P</i> < 0.05 compared with TBI. (C and D) The contractile frequency and tension were also decreased after TBI, **<i>P</i> < 0.01 compared with control. <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated decreases of contractile frequency and tension, #<i>P</i> < 0.05 compared with TBI. (E) The intestinal transit rate was decreased after TBI, **<i>P</i> < 0.01 compared with control. <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated decrease of intestinal transit rate, ##<i>P</i> < 0.01 compared with TBI.</p

<i>Lactobacillus acidophilus</i> attenuated TBI-mediated reduction of MLCK.

<p>The interaction of <i>Lactobacillus acidophilus</i> and time on MLCK protein concentrations was not significant. (A) ELISA analysis showed that the concentrations of MLCK in intestinal smooth muscle were significantly decreased after TBI, *<i>P</i> < 0.05 compared with control. <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated reduction of MLCK concentrations, ##<i>P</i> < 0.01 compared with TBI. (B) Immunohistochemistry analysis showed that marked decreases in MLCK were observed in intestinal smooth muscle after TBI, and treatment with <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated inhibition of MLCK.</p

<i>Lactobacillus acidophilus</i> could increase the MLC₂₀ phosphorylation.

<p>The interaction of <i>Lactobacillus acidophilus</i> and time on MLC₂₀ phosphorylation was not significant. (A and B) The levels of phospho-MLC₂₀ in intestinal smooth muscle were significantly decreased after TBI, *<i>P</i> < 0.05 compared with control. Treating with <i>Lactobacillus acidophilus</i> attenuated TBI-mediated inhibition of MLC₂₀ phosphorylation, #<i>P</i> < 0.05 compared with TBI. (C) The marked decreases in immunoreactivity for phospho-MLC₂₀ were observed in intestinal smooth muscle after TBI, and treatment with <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated inhibition of MLC₂₀ phosphorylation.</p

<i>Lactobacillus acidophilus</i> improved the morphology of villus.

<p>The intestinal sections from control mice presented intact structures with complete intestinal mucosae and villi (3A, 3D and 3G). TBI caused abnormal intestinal wall morphology and damaged the intestinal villi and structural integrity (3B, 3E and 3H). <i>Lactobacillus acidophilus</i> recovered intestinal mucosae and restructured villi (3C, 3F and 3I).</p

<i>Lactobacillus acidophilus</i> attenuated TBI-mediated decrease in levels of phospho-MYPT1 and increases in PKC protein concentrations.

<p>The interaction of <i>Lactobacillus acidophilus</i> and time on phospho-MYPT1 concentrations was not significant. (A and B) A marked decreases in phospho-MYPT1 were observed in intestinal smooth muscle after TBI, **<i>P</i> < 0.01 compared with control. Treatment with <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated inhibition of MYPT1 phosphorylation, ##<i>P</i> < 0.01 compared with TBI. The interaction of <i>Lactobacillus acidophilus</i> and time on PKC protein concentrations was significant. (C) ELISA analysis showed that the concentrations of PKC were increased in intestinal smooth muscle after TBI, *<i>P</i> < 0.05 compared with control. <i>Lactobacillus acidophilus</i> significantly attenuated TBI-mediated induction of PKC protein concentrations, #<i>P</i> < 0.05 compared with TBI.</p

Image_2_Cuproptosis depicts tumor microenvironment phenotypes and predicts precision immunotherapy and prognosis in bladder carcinoma.tiff

BackgroundThough immune checkpoint inhibitors (ICIs) exhibit durable efficacy in bladder carcinomas (BLCAs), there are still a large portion of patients insensitive to ICIs treatment.MethodsWe systematically evaluated the cuproptosis patterns in BLCA patients based on 46 cuproptosis related genes and correlated these cuproptosis patterns with tumor microenvironment (TME) phenotypes and immunotherapy efficacies. Then, for individual patient’s evaluation, we constructed a cuproptosis risk score (CRS) for prognosis and a cuproptosis signature for precise TME phenotypes and immunotherapy efficacies predicting.ResultsTwo distinct cuproptosis patterns were generated. These two patterns were consistent with inflamed and noninflamed TME phenotypes and had potential role for predicting immunotherapy efficacies. We constructed a CRS for predicting individual patient’s prognosis with high accuracy in TCGA-BLCA. Importantly, this CRS could be well validated in external cohorts including GSE32894 and GSE13507. Then, we developed a cuproptosis signature and found it was significantly negative correlated with tumor-infiltrating lymphocytes (TILs) both in TCGA-BLCA and Xiangya cohorts. Moreover, we revealed that patients in the high cuproptosis signature group represented a noninflamed TME phenotype on the single cell level. As expected, patients in the high cuproptosis signature group showed less sensitive to immunotherapy. Finally, we found that the high and low cuproptosis signature groups were consistent with luminal and basal subtypes of BLCA respectively, which validated the role of signature in TME in terms of molecular subtypes.ConclusionsCuproptosis patterns depict different TME phenotypes in BLCA. Our CRS and cuproptosis signature have potential role for predicting prognosis and immunotherapy efficacy, which might guide precise medicine.</p